Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds one genuinely useful trait beyond that: results come from a real algorithm engine rather than LLM generation. It says nothing about runtime, dataset size limits, or how defaults are chosen when no thresholds are supplied.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Four short clauses, front-loaded with the bracketed topic and the user scenario before the return statement. Little waste, though the bracketed label partially duplicates the annotation title.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the return value (DEG list), which matters since there is no output schema, and it names the input artifact. However, with five parameters—all optional, which is unusual for an analysis requiring two expression matrices—an agent gets no guidance on which inputs are actually needed for a valid run.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so each of the five parameters is already labeled in the schema; baseline 3 applies. The description adds no meaning beyond that—it does not explain what happens when pval_threshold or log2fc_threshold are omitted, nor what format group_a/group_b CSV strings must take.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource: differential expression analysis over an expression matrix producing a DEG list, plus volcano plot support. Clear on its own, but it never distinguishes itself from the very close sibling act_rnaseq_deg, so an agent cannot route between the two from the description alone.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase '用户有表达矩阵要做差异基因分析' implies the precondition (user has an expression matrix), which is mild usage context. There is no when-not guidance, no prerequisites, and no mention of the alternative tools (act_rnaseq_deg, act_atac_diff, act_metabo_volcano) that compete for the same request.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.